trackmania: Fictional "Trackmania" Racing Data for Interrupted...
In clinicalsignificance: A Toolbox for Clinical Significance Analyses in Intervention Studies
trackmania R Documentation
Fictional "Trackmania" Racing Data for Interrupted Time-Series
Description
A simulated dataset for an interrupted time-series (ITS) design. The data
follows two groups of race car drivers ("Training" and "Control") over 10
lap attempts. An intervention occurs after the 5th attempt, designed to
affect both the immediate performance (jump) and the subsequent learning
rate (slope change) of the Training group.
Usage
trackmania
Format
A tibble with 400 rows and 4 variables:
- driver_id
An integer representing the unique identifier for each driver.
- group
A character vector indicating the experimental group ("Training" or "Control").
- attempt
An integer representing the lap attempt number (from 1 to 10).
- lap_time_sec
A numeric value for the outcome, the lap time in seconds.
Source
Simulated data from a time-series model including fixed effects for a
pre-intervention slope, a post-intervention jump, and a post-intervention
slope change, plus random effects for driver talent (intercept) and
learning rate (slope).
clinicalsignificance documentation built on Nov. 27, 2025, 5:06 p.m.
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| trackmania | R Documentation |
Fictional "Trackmania" Racing Data for Interrupted Time-Series
Description
A simulated dataset for an interrupted time-series (ITS) design. The data follows two groups of race car drivers ("Training" and "Control") over 10 lap attempts. An intervention occurs after the 5th attempt, designed to affect both the immediate performance (jump) and the subsequent learning rate (slope change) of the Training group.
Usage
trackmania
Format
A tibble with 400 rows and 4 variables:
- driver_id
An integer representing the unique identifier for each driver.
- group
A character vector indicating the experimental group (
"Training"or"Control").- attempt
An integer representing the lap attempt number (from 1 to 10).
- lap_time_sec
A numeric value for the outcome, the lap time in seconds.
Source
Simulated data from a time-series model including fixed effects for a pre-intervention slope, a post-intervention jump, and a post-intervention slope change, plus random effects for driver talent (intercept) and learning rate (slope).
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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